A systematic review of big data innovations in smart grids

被引：22
作者：
Taherdoost, Hamed [1 ,2 ]
机构：
[1] Univ Canada West, Vancouver, BC, Canada
[2] Global Univ Syst, GUS Inst, London, England
来源：
RESULTS IN ENGINEERING | 2024年 / 22卷
关键词：
Data science; Smart environment; Big data analytics; Energy management; Demand response; DATA ANALYTICS; ARTIFICIAL-INTELLIGENCE; KNOWLEDGE EXTRACTION; INDUSTRY; 4.0; DATA SCIENCE; CHALLENGES; FRAMEWORK; CITY; MANAGEMENT; BLOCKCHAIN;
D O I：
10.1016/j.rineng.2024.102132
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Multiple industries have been revolutionized by the incorporation of data science advancements into intelligent environment technologies, specifically in the context of smart grids. Smart grids offer a dynamic and efficient framework for the management and optimization of electricity generation, distribution, and consumption, thanks to developments in big data analytics. This review delves into the integration of Smart Grid applications and Big Data analytics by reviewing 25 papers screened with PRISMA standard. The paper matter encompasses critical domains including adaptive energy management, canonical correlation analysis, and novel methodologies including blockchain and machine learning. The paper emphasizes contributions to energy efficiency, security, and sustainability by means of a rigorous methodology.
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页数：13
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